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Article

A Methodology for Evaluating Real-time Crash Risks in Driving Big Data Era

차량 주행 빅데이터 수집 환경에서 사고위험도 통합 평가 방법론 개발

Young JO1
,
Cheol OH2*
,
Jieun KO3
,
Yunjong KIM1
,
Juneyoung PARK4
조 영1
,
오 철2*
,
고 지은3
,
김 윤종1
,
박 준영4
1Ph.D Course, Transportation and Logistics Engineering, Hanyang University, Gyeonggi 15588, Korea
2Professor, Transportation and Logistics Engineering, Hanyang University, Gyeonggi 15588, Korea
3Master’s Degree, Transportation and Logistics Engineering, Hanyang University, Gyeonggi 15588, Korea
4Assistant Professor, Transportation and Logistics Engineering, Hanyang University, Gyeonggi 15588, Korea
1한양대학교 교통 ‧ 물류공학과 박사과정
2한양대학교 교통 ‧ 물류공학과 교수
3한양대학교 교통 ‧ 물류공학과 석박사통합과정
4한양대학교 교통 ‧ 물류공학과 조교수
* Corresponding Author
31 August 2019. pp. 350-364
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Abstract

The development of vehicle sensor technologies has made it possible to collect driving big data for individual vehicles. Research on surrogate safety measures (SSM) for the development of active and effective crash countermeasures has been widely carried out. This study developed an indicator for estimating the integrated crash risk consisting of the probability of rear-end crash and seriously injured. VISSIM simulation was performed to analyze the integrated crash risk for crash and non-crash scenarios. Results show that the integrated crash risk is higher at the on/off ramp than the freeway mainline, and the risk of the upstream increases during accident. A risk rate defined as the proportion of crash risks higher than the average in was used the time-space diagram to quantitatively analyze the proposed integrated crash risks. It was analyzed that the risk rate increased about 12% with crash case. The results of this study are expected to be used in developing systematically countermeasures for accident prevention and severity reduction.

Keywords
driving big data
integrated crash risk
probability of rear-end crash
probability of seriously injured
traffic safety
VISSIM

차량 검지기술의 발전과 함께 개별차량에 대한 주행 빅데이터 수집이 가능함에 따라 능동적이고 효과적인 교통사고 대응책 개발을 위한 교통안전대체지표(Surrogate Safety Measure, SSM)에 대한 연구가 지속적으로 수행되고 있다. 따라서 본 연구의 목적은 실시간으로 개별차량의 후미추돌 사고위험도를 계량화하여 통합 평가할 수 있는 지표를 개발하는 것이다. 조건부확률 및 확률의 곱셈법칙을 적용하여 후미추돌 사고발생 확률과 심각한 상해발생 확률을 고려한 개별차량의 통합사고위험도를 산출하였다. 본 연구의 분석방법론을 적용하기 위하여 미시교통류시뮬레이션인 VISSIM을 통해 네트워크 환경을 구현하고, 사고 유무에 따른 시나리오에 대해 후미추돌 사고위험도를 산출하였다. 개별차량의 사고위험도에 대해 시 ‧ 공간을 기반으로 셀 단위로 집계한 결과, 고속도로 본선보다 유출입 연결로에서 통합사고위험도가 높은 것으로 나타났으며, 특히 사고발생 후 상류부의 통합사고위험도가 증가하는 것으로 분석되었다. 사고발생 시 통합사고위험도에 미치는 영향을 정량적으로 분석하기 위하여 시공도의 전체 셀의 개수 중 통합사고위험도 평균 값 이상의 셀의 비율을 Risk rate로 정의하였다. 분석결과, 사고로 인한 차로 통제 상황에서 Risk rate가 약 12% 증가하는 것으로 분석되었다. 본 연구의 결과는 개별차량의 사고 개연성 및 심각한 상해발생 확률을 정량적으로 분석함으로써 사고 예방 및 심각도 감소를 위한 체계적인 대응방안을 마련하는데 활용될 것으로 기대된다.

키워드
주행 빅데이터
통합사고위험도
후미추돌 사고발생 확률
심각한 상해발생 확률
교통안전성
미시교통류시뮬레이션
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Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 37
  • No :4
  • Pages :350-364
  • Received Date : 2019-07-03
  • Revised Date : 2019-07-30
  • Accepted Date : 2019-08-23
  • DOI :https://doi.org/10.7470/jkst.2019.37.4.350
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